One known sort operating mode is described below in reference to FIG. 1.
The user terminals U1 to Uk are for example mobile telephones. They have access, through a 3G or Wi-Fi wireless communication network, to a platform of services S1, S2, . . . Ss. The services, delivered by service providers, for example comprise applications, sites or webpages. The mobile telephones are equipped with a software application of the “cookie” type, which copies the elements entered or selected by the user during operational use of the telephone to request or use services delivered by the platform, as well as services or applications that are local to the terminal or outside the platform. The software application transmits those elements to the analysis engine 2.
Thus, when the users of the user terminals U1 to Uk write e-mails, SMS messages or keywords in a search engine, select Internet links, enter information on Facebook pages, or browse selected websites, all of those elements are transmitted to the platform of services to perform the concerned service, respectively sending e-mails or SMS (“short message service”) or MMS (“multimedia message service”) messages, providing results for the keyword search, displaying selected websites, or updating the Facebook page. Furthermore, these elements, which are associated with an identifier of the device (or similarly an identifier of the user), are transmitted to the analysis engine 2 in parallel.
When the analysis engine 2 receives these format and/or content elements of varied and unknown natures, it determines, according to the identifier associated with the elements, the sorting search or searches to be done on the various elements.
The sorting searches are therefore done from data whereof the form, nature and meaning are unknown. These searches may be varied and may aim to characterize the age, gender, areas of interest and/or expectations of the user in terms of quality/speed of service, technical constraints encountered, etc.
In one example, a first sorting search serves to select a class from among the following: “child,” “adult,” “senior.” Another sorting search for example serves to select a class from among the following: “soccer fan,” “golf fan,” “cycling fan,” “tennis fan.”
Once the sorting search, called RCA, to be conducted on elements associated with an identifier is determined, the analysis engine 2 analyzes those elements using rules, keywords, algorithms, dictionaries, grammars, present in the database 3 so as to select the relevant class from among the different classes, called CRCA1, CRCA2, . . . , CRCAn associated with that sorting search.
One or more actions are then triggered intended for the considered user terminal, depending on the class selected for that user terminal.
The Google analytics tool is also known.
Furthermore, document WO 01/20481 describes a system for determining the profiles of users using the user terminals to browse the web. According to this document, a remote POP (“Point Of Presence”) server providing Internet access collects and stores the URL (“Uniform Resource Locator”) address requests transmitted by the terminals matched with the users' identifiers. An analysis engine (“client profiling component”) of the POP server then next determines a profile for the users, or updates it, based on the collected data and information from a database containing a copy of a database from the so-called master server. This information contains demographic characteristics allocated to URL addresses, such as those corresponding to the “Nielsen Net Ratings” service. The Nielsen Net Ratings data are established by observing a sample of the population and noting the sites they visit: profiles are associated with particular websites.
These techniques nevertheless have a certain number of drawbacks.
First, the elements entered by the user during operational use of the mobile telephone are sent to a remote server, in association with the user's identifier, which poses major security and confidentiality issues, since these elements may include information that the user does not wish to have disclosed in this way. Encrypting the transmission does not prevent the possibility of fraudulent use of the information at the analysis server, particularly given that those elements are frequently stored for a certain amount of time so as to be reused by the server to refine the sorting done in a first stage.
Such a transmission of information without prior consent from the users is also detrimental.
Furthermore, the processing done by the analysis engine requires a very significant volume of computation resources, and the volume of the database is also quite significant.